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Public-Private Innovation Partnerships (PPIPs) are increasingly used as a tool for addressing ‘wicked’ public sector challenges. ‘Innovation’ is, however, frequently treated as a ‘magic’ concept: used unreflexively, taken to be axiomatically ‘good’, and left undefined within policy programmes. Using McConnell’s framework of policy success and failure and a case study of a multi-level PPIP in the English health service (NHS Test Beds), this paper critically explores the implications of the mobilisation of innovation in PPIP policy and practice. We highlight how the interplay between levels (macro/micro and policy maker/recipient) can shape both emerging policies and their prospects for success or failure. The paper contributes to an understanding of PPIP success and failure by extending McConnell’s framework to explore inter-level effects between policy and innovation project, and demonstrating how the success of PPIP policy cannot be understood without recognising the particular political effects of ‘innovation’ on formulation and implementation.
In this article I caution that María Lugones's critiques of Kimberlé Crenshaw's intersectional theory posit a dangerous form of epistemic erasure, which underlies Lugones's decolonial methodology. This essay serves as a critical engagement with Lugones's essay “Radical Multiculturalism and Women of Color Feminisms” in order to uncover the decolonial lens within Crenshaw's theory of intersectionality. In her assertion that intersectionality is a “white bourgeois feminism colluding with the oppression of Women of Color,” Lugones precludes any possibility of intersectionality operating as a decolonial method. Although Lugones states that her “decolonial feminism” is for all women of color, it ultimately excludes Black women, particularly with her misconstruing of Crenshaw's articulation of intersectionality that is rooted within the Black American feminist tradition. I explore Lugones's claims by juxtaposing her rendering of intersectionality with Crenshaw's and conclude that Lugones's decolonial theory risks erasing Black women from her framework.
In the present study, we aimed to compare anthropometric indicators as predictors of mortality in a community-based setting.
We conducted a population-based longitudinal study nested in a cluster-randomized trial. We assessed weight, height and mid-upper arm circumference (MUAC) on children 12 months after the trial began and used the trial’s annual census and monitoring visits to assess mortality over 2 years.
Children aged 6–60 months during the study.
Of 1023 children included in the study at baseline, height-for-age Z-score, weight-for-age Z-score, weight-for-height Z-score and MUAC classified 777 (76·0 %), 630 (61·6 %), 131 (12·9 %) and eighty (7·8 %) children as moderately to severely malnourished, respectively. Over the 2-year study period, fifty-eight children (5·7 %) died. MUAC had the greatest AUC (0·68, 95 % CI 0·61, 0·75) and had the strongest association with mortality in this sample (hazard ratio = 2·21, 95 % CI 1·26, 3·89, P = 0·006).
MUAC appears to be a better predictor of mortality than other anthropometric indicators in this community-based, high-malnutrition setting in Niger.
Background: Cervical sponylotic myelopathy (CSM) may present with neck and arm pain. This study investiagtes the change in neck/arm pain post-operatively in CSM. Methods: This ambispective study llocated 402 patients through the Canadian Spine Outcomes and Research Network. Outcome measures were the visual analogue scales for neck and arm pain (VAS-NP and VAS-AP) and the neck disability index (NDI). The thresholds for minimum clinically important differences (MCIDs) for VAS-NP and VAS-AP were determined to be 2.6 and 4.1. Results: VAS-NP improved from mean of 5.6±2.9 to 3.8±2.7 at 12 months (P<0.001). VAS-AP improved from 5.8±2.9 to 3.5±3.0 at 12 months (P<0.001). The MCIDs for VAS-NP and VAS-AP were also reached at 12 months. Based on the NDI, patients were grouped into those with mild pain/no pain (33%) versus moderate/severe pain (67%). At 3 months, a significantly high proportion of patients with moderate/severe pain (45.8%) demonstrated an improvement into mild/no pain, whereas 27.2% with mild/no pain demonstrated worsening into moderate/severe pain (P <0.001). At 12 months, 17.4% with mild/no pain experienced worsening of their NDI (P<0.001). Conclusions: This study suggests that neck and arm pain responds to surgical decompression in patients with CSM and reaches the MCIDs for VAS-AP and VAS-NP at 12 months.
Background: Cervical spondylotic myelopathy (CSM) is the leading cause of spinal cord impairment. In a public healthcare system, wait times to see spine specialists and eventually access surgical treatment for CSM can be substantial. The goals of this study were to determine consultation wait times (CWT) and surgical wait times (SWT), and identify predictors of wait time length. Methods: Consecutive patients enrolled in the Canadian Spine Outcomes and Research Network (CSORN) prospective and observational CSM study from March 2015 to July 2017 were included. A data-splitting technique was used to develop and internally validate multivariable models of potential predictors. Results: A CSORN query returned 264 CSM patients for CWT. The median was 46 days. There were 31% mild, 35% moderate, and 33% severe CSM. There was a statistically significant difference in median CWT between moderate and severe groups; 207 patients underwent surgical treatment. Median SWT was 42 days. There was a statistically significant difference in SWT between mild/moderate and severe groups. Short symptom duration, less pain, lower BMI, and lower physical component score of SF-12 were predictive of shorter CWT. Only baseline pain and medication duration were predictive of SWT. Both CWT and SWT were shorter compared to a concurrent cohort of lumbar stenosis patients (p <0.001). Conclusions: Patients with shorter duration (either symptoms or medication) and less neck pain waited less to see a spine specialist in Canada and to undergo surgical treatment. This study highlights some of the obstacles to overcome in expedited care for this patient population.
Nitrous oxide (N2O) is a potent greenhouse gas with implication
for climate change. Agriculture accounts for 10% of all greenhouse gas
emissions in the United States, but 75% of the country's N2O
emissions. In the absence of PRE herbicides, weeds compete with soybean for
available soil moisture and inorganic N, and may reduce N2O
emissions relative to a weed-free environment. However, after weeds are
killed with a POST herbicide, the dead weed residues may stimulate
N2O emissions by increasing soil moisture and supplying carbon
and nitrogen to microbial denitrifiers. Wider soybean rows often have more
weed biomass, and as a result, row width may further impact how weeds
influence N2O emissions. To determine this relationship, field
studies were conducted in 2013 and 2014 in Arlington, WI. A two-by-two
factorial treatment structure of weed management (PRE + POST vs. POST-only)
and row width (38 or 76 cm) was arranged in a randomized complete block
design with four replications. N2O fluxes were measured from
static gas sampling chambers at least weekly starting 2 wk after planting
until mid-September, and were compared for the periods before and after weed
termination using a repeated measures analysis. N2O fluxes were
not influenced by the weed by width
interaction or width before termination, after termination,
or for the full duration of the study at P ≤ 0.05. Interestingly, we
observed that POST-only treatments had lower fluxes on the sampling day
immediately prior to POST application (P = 0.0002), but this was the only
incidence where weed influenced N2O fluxes, and
overall, average fluxes from PRE + POST and POST-only treatments were not
different for any period of the study. Soybean yield was not influenced by
width (P = 0.6018) or weed by
width (P = 0.5825), but yield was 650 kg ha−1
higher in the PRE + POST than POST-only treatments (P = 0.0007). These
results indicate that herbicide management strategy does not influence
N2O emissions from soybean, and the use of a PRE herbicide
prevents soybean yield loss.
This paper describes the independent construction and implementation of two cellular automata that model dialect feature diffusion as the adaptive aspect of the complex system of speech. We show how a feature, once established, can spread across an area, and how the distribution of a dialect feature as it stands in Linguistic Atlas data could either spread or diminish. Cellular automata use update rules to determine the status of a feature at a given location with respect to the status of its neighboring locations. In each iteration all locations in a matrix are evaluated, and then the new status for each one is displayed all at once. Throughout hundreds of iterations, we can watch regional distributional patterns emerge as a consequence of these simple update rules. We validate patterns with respect to the linguistic distributions known to occur in the Linguistic Atlas Project.